About Me

• Single cell omics analysis
• VQ-VAE / Discrete Representation / Machine unlearning

Predict the area ratio of planets and stars and the confidence level (uncertainty) sigma.

• Achieved the 7th(1%) in the NeurIPS Competition. Achieve my first gold medal.
• We have developed a method that spans from heuristic forward modeling to Gaussian processes, to deep learning, and to gradient boosting trees.
• Become Kaggle Competition Masters.

Reconstruct the direction of neutrinos from the Universe to the South Pole

• Achieved the 21th in the Neutrinos and Astrophysics competition, ranking in the top 3% globally among all participating teams.
• Utilized a 3D point cloud convolution model based on the EdgeConv operator, developed various RNN models, and employed a multi-stage training method grounded in IceCube’s physical principles.
• This achievement also marks my first medal in Kaggle competitions.

Developed a model trained on Electroencephalography (EEG) signals and Spectrogram recorded from critically ill hospital patients to classify a variety of harmful brain activities.

• Achieved 38th place in the Neuroscience and Physiology competition, ranking in the top 2% globally among all participating teams.
• Developed a 1D model based on EEG signals and employed innovative training methods to create an effective 1D+2D multi-modal model.